Text Classification
Transformers
PyTorch
English
distilbert
classification
text-embeddings-inference
Instructions to use lingwave-admin/state-op-detector with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use lingwave-admin/state-op-detector with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="lingwave-admin/state-op-detector")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("lingwave-admin/state-op-detector") model = AutoModelForSequenceClassification.from_pretrained("lingwave-admin/state-op-detector", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Commit History
-
Adding `safetensors` variant of this model
a561514
-
Added contact info
9c50f3f
-
Added metadata and example text
b070da1
-
Created readme.md
22ef733
-
Update config.json
2b5067d -
Update config.json
9d0f6d8 -
Update config.json
53ec512 -
Update config.json
99b7eee -
Retrained model with no retweets and much larger sample of natural tweets.
8ef4978
-
Added new version of model trained on Tweets with topics matching those mentioned in state operator tweets.
00cb705
-
Initial model version
0a121fd -
Upload config.json
31d2aa8
-
initial commit
eb272a8